The Metric Interquartile command is used to find the range of the middle 50% of datapoints within a set. A quartile is a statistical measure that divides a data set into four equal parts, with each part representing 25% of the observations. There are three quartile values: the first quartile (Q1), which marks the 25th percentile; the second quartile (Q2), which is the median; and the third quartile (Q3), which marks the 75th percentile. The interquartile range can be defined as Q3-Q1 and can be helpful when analyzing the variability of data and/or identifying outliers.

Read more here.

The command can be found in the Pipeline Workshop under Metric as so:

Metric_Interquartile
! /RESULT_METRIC_FOLDER=PROCESSED
/RESULT_METRIC_NAME=
! /APPLY_AS_SUFFIX_TO_SIGNAL_NAME=FALSE
/SIGNAL_TYPES=
! /SIGNAL_FOLDER=ORIGINAL
! /SIGNAL_NAMES=
! /COMPONENT_SEQUENCE=
/EVENT_SEQUENCE=
/EXCLUDE_EVENTS=
! /GENERATE_MEAN_AND_STDDEV=TRUE
! /GENERATE_MEAN_AND_STDDEV_ACROSS_SUBJECTS=FALSE
! /APPEND_TO_EXISTING_VALUES=FALSE
;

The following table shows the command parameters seen above and their descriptions:

The command can be edited in a text editor or in a dialog form. To edit in the dialog pop up form either click on the Edit button in the pipeline workshop or double-click on the pipeline command. The dialog is shown below:

The dialog box allows you to assign values to the command parameters outlined above.

Here the Metric Interquartile command is used to analyze center of foot pressure data during a standing trial and compare the ranges computed for a subject's left and right sides.

The command for the right side looks like this:

Metric_Interquartile
! /RESULT_METRIC_FOLDER=PROCESSED
/RESULT_METRIC_NAME=COFP_RIGHT_INTER
! /APPLY_AS_SUFFIX_TO_SIGNAL_NAME=FALSE
/SIGNAL_TYPES=COFP
! /SIGNAL_FOLDER=ORIGINAL
/SIGNAL_NAMES=FP3
 /COMPONENT_SEQUENCE=ALL
/EVENT_SEQUENCE=START+END
/EXCLUDE_EVENTS=
! /GENERATE_MEAN_AND_STDDEV=TRUE
! /GENERATE_MEAN_AND_STDDEV_ACROSS_SUBJECTS=FALSE
! /APPEND_TO_EXISTING_VALUES=FALSE
;

COFP is a 2 dimensional signal, with the X and y components representing the medial/lateral and anterior/posterior directions respectively. The resulting metrics contain an x value and a y value indicating the variation in pressure for each direction during the trial. A larger range indicates greater variation in the COFP value during the trial and a less consistent balance point.

The results for this trial show a larger range for the right side than left and a greater range in the Y direction than X for both sides.

In this example Metric Interquartile is used to compare the left and right ankle angles of subjects running on a treadmill.

First, Automatic Gait Events is used to define key events that will define the following commands:

Automatic_Gait_Events
! /FRAME_WINDOW=8
! /USE_TPR=TRUE
! /TPR_EVENT_INSTANCE=1
;

Next, the Interquartile command is used to identify the middle 50% range of ankle angle values for both sides between toe and heel strikes.

Metric_Interquartile
! /RESULT_METRIC_FOLDER=PROCESSED
/RESULT_METRIC_NAME=RANKLE_INTER
! /APPLY_AS_SUFFIX_TO_SIGNAL_NAME=FALSE
/SIGNAL_TYPES=LINK_MODEL_BASED
! /SIGNAL_FOLDER=ORIGINAL
/SIGNAL_NAMES=RAnkleAngle
! /COMPONENT_SEQUENCE=
/EVENT_SEQUENCE=RHS+RTO
/EXCLUDE_EVENTS=
! /GENERATE_MEAN_AND_STDDEV=TRUE
! /GENERATE_MEAN_AND_STDDEV_ACROSS_SUBJECTS=FALSE
! /APPEND_TO_EXISTING_VALUES=FALSE
;

Metric_Interquartile
! /RESULT_METRIC_FOLDER=PROCESSED
/RESULT_METRIC_NAME=LANKLE_INTER
! /APPLY_AS_SUFFIX_TO_SIGNAL_NAME=FALSE
/SIGNAL_TYPES=LINK_MODEL_BASED
! /SIGNAL_FOLDER=ORIGINAL
/SIGNAL_NAMES=LAnkleAngle
! /COMPONENT_SEQUENCE=
/EVENT_SEQUENCE=LHS+LTO
/EXCLUDE_EVENTS=
! /GENERATE_MEAN_AND_STDDEV=TRUE
! /GENERATE_MEAN_AND_STDDEV_ACROSS_SUBJECTS=FALSE
! /APPEND_TO_EXISTING_VALUES=FALSE
;

The results for this trial show that the subjects on average exhibited a larger interquartile range for flexion of their left ankles than right.